RRepoGEO

REPOGEO REPORT · LITE

IDEA-Research/Rex-Omni

Default branch master · commit 6508981c · scanned 6/22/2026, 8:27:59 AM

GitHub: 1,455 stars · 103 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
40 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 warn · 0 fail
Objective metadata checks
AI knows your name
3 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface IDEA-Research/Rex-Omni, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • mediumlicense#1
    Add a clear statement about the project's license(s) to the README

    Why:

    COPY-PASTE FIX
    ## License
This project is released under [specify license(s), e.g., a custom research license or a combination of licenses]. Please refer to the LICENSE file for full details.
  • lowabout#2
    Update repository description to highlight MLLM and open-set object detection

    Why:

    CURRENT
    [CVPR2026] Detect Anything via Next Point Prediction
    COPY-PASTE FIX
    [CVPR2026] Rex-Omni: A Multimodal LLM for Next Point Prediction & Open-Set Object Detection

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface IDEA-Research/Rex-Omni
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
OWL-ViT
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. OWL-ViT · recommended 2×
  2. GPT-4V · recommended 1×
  3. Google Gemini · recommended 1×
  4. Llama 3 · recommended 1×
  5. CLIP · recommended 1×
  • CATEGORY QUERY
    How can I leverage multimodal large language models for various visual perception tasks?
    you: not recommended
    AI recommended (in order):
    1. GPT-4V
    2. Google Gemini
    3. Llama 3
    4. CLIP
    5. ViT
    6. BLIP-2
    7. OWL-ViT
    8. DALL-E 3
    9. ChatGPT
    10. Midjourney
    11. OpenFlamingo

    AI recommended 11 alternatives but never named IDEA-Research/Rex-Omni. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a robust open-set object detection model capable of identifying novel categories.
    you: not recommended
    AI recommended (in order):
    1. OWL-ViT
    2. Grounding DINO
    3. GLIP
    4. ViLD
    5. OFA

    AI recommended 5 alternatives but never named IDEA-Research/Rex-Omni. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    pass

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of IDEA-Research/Rex-Omni?
    pass
    AI named IDEA-Research/Rex-Omni explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts IDEA-Research/Rex-Omni in production, what risks or prerequisites should they evaluate first?
    pass
    AI named IDEA-Research/Rex-Omni explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo IDEA-Research/Rex-Omni solve, and who is the primary audience?
    pass
    AI named IDEA-Research/Rex-Omni explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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IDEA-Research/Rex-Omni — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite